Corcoran, Padraig and Winstanley, Adam C. and Mooney, Peter and Middleton, Rick (2011) Background Foreground Segmentation for SLAM. IEEE Transactions on Intelligent Transportation Systems, 12 (4). ISSN 1524-9050

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Abstract

To perform simultaneous localization and mapping (SLAM) in dynamic environments, static background objects must first be determined. This condition can be achieved using a priori information in the form of a map of background objects. Such an approach exhibits a causality dilemma, because such a priori information is the ultimate goal of SLAM. In this paper, we propose a background foreground segmentation method that overcomes this issue. Localization is achieved using a robust iterative closest point implementation and vehicle odometry. Background objects are modeled as objects that are consistently located at a given spatial location. To improve robustness, classification is performed at the object level through the integration of a new segmentation method that is robust to partial object occlusion.

Item Type:	Article
Keywords:	Background–Foreground segmentation; light detection and ranging; LIDAR;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	4489
Depositing User:	Dr. Adam Winstanley
Date Deposited:	16 Sep 2013 13:57
Journal or Publication Title:	IEEE Transactions on Intelligent Transportation Systems
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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